Overview

Dataset statistics

Number of variables26
Number of observations33120
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.6 MiB
Average record size in memory208.0 B

Variable types

NUM16
CAT10

Warnings

$10,000-$14,999 has a high cardinality: 523 distinct values High cardinality
$15,000-$24,999 has a high cardinality: 419 distinct values High cardinality
$25,000-$34,999 has a high cardinality: 554 distinct values High cardinality
$35,000-$49,999 has a high cardinality: 520 distinct values High cardinality
$50,000-$64,999 has a high cardinality: 564 distinct values High cardinality
$65,000-$74,999 has a high cardinality: 615 distinct values High cardinality
$75,000-$99,999 has a high cardinality: 507 distinct values High cardinality
$100,000_or_more has a high cardinality: 831 distinct values High cardinality
median_household_income has a high cardinality: 19384 distinct values High cardinality
mean_household_income has a high cardinality: 25781 distinct values High cardinality
5-9_years is highly correlated with 5_years_or_less and 6 other fieldsHigh correlation
5_years_or_less is highly correlated with 5-9_years and 10 other fieldsHigh correlation
10-14_years is highly correlated with 5_years_or_less and 7 other fieldsHigh correlation
15-19_years is highly correlated with 5_years_or_less and 7 other fieldsHigh correlation
20-24_years is highly correlated with 5_years_or_less and 3 other fieldsHigh correlation
25-34_years is highly correlated with 20-24_yearsHigh correlation
35-44_years is highly correlated with 5_years_or_less and 4 other fieldsHigh correlation
45-54_years is highly correlated with 5_years_or_less and 8 other fieldsHigh correlation
55-59_years is highly correlated with 5_years_or_less and 9 other fieldsHigh correlation
60-64_years is highly correlated with 5_years_or_less and 7 other fieldsHigh correlation
65-74_years is highly correlated with 5_years_or_less and 6 other fieldsHigh correlation
75-84_years is highly correlated with 5_years_or_less and 5 other fieldsHigh correlation
85_years_or_more is highly correlated with 65-74_years and 2 other fieldsHigh correlation
households is highly correlated with 85_years_or_moreHigh correlation
$9,999_or_less is highly correlated with 5_years_or_less and 9 other fieldsHigh correlation
zipcode has unique values Unique
5-9_years has 2989 (9.0%) zeros Zeros
10-14_years has 2765 (8.3%) zeros Zeros
15-19_years has 2577 (7.8%) zeros Zeros
20-24_years has 2298 (6.9%) zeros Zeros
25-34_years has 2662 (8.0%) zeros Zeros
35-44_years has 1698 (5.1%) zeros Zeros
45-54_years has 1564 (4.7%) zeros Zeros
55-59_years has 1194 (3.6%) zeros Zeros
60-64_years has 1619 (4.9%) zeros Zeros
65-74_years has 1686 (5.1%) zeros Zeros
75-84_years has 1359 (4.1%) zeros Zeros
85_years_or_more has 2234 (6.7%) zeros Zeros
households has 4600 (13.9%) zeros Zeros
$9,999_or_less has 571 (1.7%) zeros Zeros

Reproduction

Analysis started2020-11-25 00:29:30.329792
Analysis finished2020-11-25 00:30:11.385707
Duration41.06 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

zipcode
Real number (ℝ≥0)

UNIQUE

Distinct33120
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49666.33421
Minimum601
Maximum99929
Zeros0
Zeros (%)0.0%
Memory size258.8 KiB
2020-11-24T19:30:11.473148image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum601
5-th percentile5849.85
Q126634.75
median49739
Q372123.5
95-th percentile95614.05
Maximum99929
Range99328
Interquartile range (IQR)45488.75

Descriptive statistics

Standard deviation27564.92577
Coefficient of variation (CV)0.5550022205
Kurtosis-1.064030546
Mean49666.33421
Median Absolute Deviation (MAD)22644.5
Skewness0.037825603
Sum1644948989
Variance759825132.7
MonotocityStrictly increasing
2020-11-24T19:30:11.595238image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
20471< 0.1%
 
487011< 0.1%
 
486371< 0.1%
 
755621< 0.1%
 
875521< 0.1%
 
240651< 0.1%
 
179221< 0.1%
 
199711< 0.1%
 
281671< 0.1%
 
56401< 0.1%
 
Other values (33110)33110> 99.9%
 
ValueCountFrequency (%) 
6011< 0.1%
 
6021< 0.1%
 
6031< 0.1%
 
6061< 0.1%
 
6101< 0.1%
 
ValueCountFrequency (%) 
999291< 0.1%
 
999271< 0.1%
 
999261< 0.1%
 
999251< 0.1%
 
999231< 0.1%
 

5_years_or_less
Real number (ℝ≥0)

HIGH CORRELATION

Distinct15534
Distinct (%)46.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9664.375151
Minimum0
Maximum114982
Zeros310
Zeros (%)0.9%
Memory size258.8 KiB
2020-11-24T19:30:11.717715image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile106
Q1718.75
median2808
Q313139.25
95-th percentile40369.05
Maximum114982
Range114982
Interquartile range (IQR)12420.5

Descriptive statistics

Standard deviation14237.94938
Coefficient of variation (CV)1.473240551
Kurtosis5.434379768
Mean9664.375151
Median Absolute Deviation (MAD)2561
Skewness2.176083804
Sum320084105
Variance202719202.4
MonotocityNot monotonic
2020-11-24T19:30:11.841674image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
03100.9%
 
186260.1%
 
247220.1%
 
81220.1%
 
149210.1%
 
280210.1%
 
146210.1%
 
142210.1%
 
141210.1%
 
123210.1%
 
Other values (15524)3261498.5%
 
ValueCountFrequency (%) 
03100.9%
 
21< 0.1%
 
33< 0.1%
 
42< 0.1%
 
53< 0.1%
 
ValueCountFrequency (%) 
1149821< 0.1%
 
1138871< 0.1%
 
1127091< 0.1%
 
1066591< 0.1%
 
1061751< 0.1%
 

5-9_years
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct3763
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean607.095622
Minimum0
Maximum16998
Zeros2989
Zeros (%)9.0%
Memory size258.8 KiB
2020-11-24T19:30:11.969297image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q133
median150
Q3754
95-th percentile2681
Maximum16998
Range16998
Interquartile range (IQR)721

Descriptive statistics

Standard deviation1004.262799
Coefficient of variation (CV)1.6542086
Kurtosis12.56140169
Mean607.095622
Median Absolute Deviation (MAD)145
Skewness2.899536148
Sum20107007
Variance1008543.77
MonotocityNot monotonic
2020-11-24T19:30:12.091377image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
029899.0%
 
102020.6%
 
82020.6%
 
62000.6%
 
41990.6%
 
71970.6%
 
191950.6%
 
121910.6%
 
131900.6%
 
51840.6%
 
Other values (3753)2837185.7%
 
ValueCountFrequency (%) 
029899.0%
 
1760.2%
 
21330.4%
 
31600.5%
 
41990.6%
 
ValueCountFrequency (%) 
169981< 0.1%
 
120981< 0.1%
 
101141< 0.1%
 
99201< 0.1%
 
98361< 0.1%
 

10-14_years
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct3806
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean625.4815821
Minimum0
Maximum13509
Zeros2765
Zeros (%)8.3%
Memory size258.8 KiB
2020-11-24T19:30:12.219563image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q137
median165
Q3794
95-th percentile2720
Maximum13509
Range13509
Interquartile range (IQR)757

Descriptive statistics

Standard deviation1004.665379
Coefficient of variation (CV)1.606226959
Kurtosis10.58738108
Mean625.4815821
Median Absolute Deviation (MAD)158
Skewness2.75689394
Sum20715950
Variance1009352.525
MonotocityNot monotonic
2020-11-24T19:30:12.349563image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
027658.3%
 
141980.6%
 
111960.6%
 
61880.6%
 
121880.6%
 
81850.6%
 
41820.5%
 
131820.5%
 
201810.5%
 
101810.5%
 
Other values (3796)2867486.6%
 
ValueCountFrequency (%) 
027658.3%
 
1630.2%
 
21290.4%
 
31530.5%
 
41820.5%
 
ValueCountFrequency (%) 
135091< 0.1%
 
102151< 0.1%
 
101611< 0.1%
 
97381< 0.1%
 
95131< 0.1%
 

15-19_years
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct3816
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean631.6319746
Minimum0
Maximum10411
Zeros2577
Zeros (%)7.8%
Memory size258.8 KiB
2020-11-24T19:30:12.481411image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q139
median175
Q3814
95-th percentile2700
Maximum10411
Range10411
Interquartile range (IQR)775

Descriptive statistics

Standard deviation998.3284436
Coefficient of variation (CV)1.580553999
Kurtosis9.540846654
Mean631.6319746
Median Absolute Deviation (MAD)167
Skewness2.672337533
Sum20919651
Variance996659.6814
MonotocityNot monotonic
2020-11-24T19:30:12.607378image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
025777.8%
 
91870.6%
 
81840.6%
 
51830.6%
 
111830.6%
 
101830.6%
 
71820.5%
 
201760.5%
 
171730.5%
 
41670.5%
 
Other values (3806)2892587.3%
 
ValueCountFrequency (%) 
025777.8%
 
1870.3%
 
21310.4%
 
31490.4%
 
41670.5%
 
ValueCountFrequency (%) 
104111< 0.1%
 
97851< 0.1%
 
93041< 0.1%
 
92971< 0.1%
 
90571< 0.1%
 

20-24_years
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct3913
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean652.501872
Minimum0
Maximum12815
Zeros2298
Zeros (%)6.9%
Memory size258.8 KiB
2020-11-24T19:30:12.734343image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q141
median177
Q3826.25
95-th percentile2833.05
Maximum12815
Range12815
Interquartile range (IQR)785.25

Descriptive statistics

Standard deviation1044.958346
Coefficient of variation (CV)1.601464134
Kurtosis11.25569317
Mean652.501872
Median Absolute Deviation (MAD)168
Skewness2.816175371
Sum21610862
Variance1091937.944
MonotocityNot monotonic
2020-11-24T19:30:12.866277image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
022986.9%
 
61990.6%
 
101970.6%
 
71960.6%
 
131940.6%
 
111920.6%
 
81910.6%
 
121820.5%
 
191820.5%
 
51780.5%
 
Other values (3903)2911187.9%
 
ValueCountFrequency (%) 
022986.9%
 
11030.3%
 
21280.4%
 
31450.4%
 
41540.5%
 
ValueCountFrequency (%) 
128151< 0.1%
 
112901< 0.1%
 
111291< 0.1%
 
108571< 0.1%
 
106421< 0.1%
 

25-34_years
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct4169
Distinct (%)12.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean690.2298309
Minimum0
Maximum24060
Zeros2662
Zeros (%)8.0%
Memory size258.8 KiB
2020-11-24T19:30:12.994823image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q133
median156
Q3798
95-th percentile3077
Maximum24060
Range24060
Interquartile range (IQR)765

Descriptive statistics

Standard deviation1262.651196
Coefficient of variation (CV)1.829319944
Kurtosis31.44537721
Mean690.2298309
Median Absolute Deviation (MAD)150
Skewness4.1776405
Sum22860412
Variance1594288.042
MonotocityNot monotonic
2020-11-24T19:30:13.121324image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
026628.0%
 
82370.7%
 
102280.7%
 
62200.7%
 
72100.6%
 
92090.6%
 
122030.6%
 
161990.6%
 
41990.6%
 
111930.6%
 
Other values (4159)2856086.2%
 
ValueCountFrequency (%) 
026628.0%
 
11110.3%
 
21860.6%
 
31770.5%
 
41990.6%
 
ValueCountFrequency (%) 
240601< 0.1%
 
227811< 0.1%
 
213351< 0.1%
 
189381< 0.1%
 
184101< 0.1%
 

35-44_years
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct6259
Distinct (%)18.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1308.378019
Minimum0
Maximum26926
Zeros1698
Zeros (%)5.1%
Memory size258.8 KiB
2020-11-24T19:30:13.241109image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q167
median292
Q31549.25
95-th percentile5952
Maximum26926
Range26926
Interquartile range (IQR)1482.25

Descriptive statistics

Standard deviation2203.234802
Coefficient of variation (CV)1.683943608
Kurtosis10.90531669
Mean1308.378019
Median Absolute Deviation (MAD)275
Skewness2.816721146
Sum43333480
Variance4854243.595
MonotocityNot monotonic
2020-11-24T19:30:13.372219image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
016985.1%
 
151370.4%
 
141360.4%
 
101350.4%
 
251330.4%
 
161300.4%
 
171280.4%
 
181280.4%
 
211280.4%
 
91250.4%
 
Other values (6249)3024291.3%
 
ValueCountFrequency (%) 
016985.1%
 
1420.1%
 
2780.2%
 
3930.3%
 
4950.3%
 
ValueCountFrequency (%) 
269261< 0.1%
 
265871< 0.1%
 
245531< 0.1%
 
230711< 0.1%
 
224961< 0.1%
 

45-54_years
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct5944
Distinct (%)17.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1241.185296
Minimum0
Maximum18739
Zeros1564
Zeros (%)4.7%
Memory size258.8 KiB
2020-11-24T19:30:13.500383image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q174
median322
Q31598
95-th percentile5413
Maximum18739
Range18739
Interquartile range (IQR)1524

Descriptive statistics

Standard deviation1951.60322
Coefficient of variation (CV)1.572370561
Kurtosis7.832544274
Mean1241.185296
Median Absolute Deviation (MAD)303
Skewness2.491705882
Sum41108057
Variance3808755.128
MonotocityNot monotonic
2020-11-24T19:30:13.620819image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
015644.7%
 
111330.4%
 
141310.4%
 
61300.4%
 
191290.4%
 
101290.4%
 
81210.4%
 
121210.4%
 
151200.4%
 
331170.4%
 
Other values (5934)3042591.9%
 
ValueCountFrequency (%) 
015644.7%
 
1350.1%
 
2790.2%
 
3710.2%
 
41110.3%
 
ValueCountFrequency (%) 
187391< 0.1%
 
184841< 0.1%
 
184081< 0.1%
 
174061< 0.1%
 
170321< 0.1%
 

55-59_years
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct6133
Distinct (%)18.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1339.541033
Minimum0
Maximum15710
Zeros1194
Zeros (%)3.6%
Memory size258.8 KiB
2020-11-24T19:30:13.748376image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8
Q199
median407
Q31833.25
95-th percentile5522
Maximum15710
Range15710
Interquartile range (IQR)1734.25

Descriptive statistics

Standard deviation1955.630562
Coefficient of variation (CV)1.459925836
Kurtosis5.391925599
Mean1339.541033
Median Absolute Deviation (MAD)377
Skewness2.169400951
Sum44365599
Variance3824490.895
MonotocityNot monotonic
2020-11-24T19:30:13.868760image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
011943.6%
 
151100.3%
 
101100.3%
 
191070.3%
 
231040.3%
 
271040.3%
 
141010.3%
 
181010.3%
 
46990.3%
 
7980.3%
 
Other values (6123)3099293.6%
 
ValueCountFrequency (%) 
011943.6%
 
1230.1%
 
2530.2%
 
3430.1%
 
4660.2%
 
ValueCountFrequency (%) 
157101< 0.1%
 
151801< 0.1%
 
147561< 0.1%
 
146671< 0.1%
 
146621< 0.1%
 

60-64_years
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct3617
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean640.6934481
Minimum0
Maximum7298
Zeros1619
Zeros (%)4.9%
Memory size258.8 KiB
2020-11-24T19:30:13.998950image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q153
median208
Q3903
95-th percentile2585
Maximum7298
Range7298
Interquartile range (IQR)850

Descriptive statistics

Standard deviation898.9681268
Coefficient of variation (CV)1.403117403
Kurtosis4.313317254
Mean640.6934481
Median Absolute Deviation (MAD)192
Skewness1.998318978
Sum21219767
Variance808143.6931
MonotocityNot monotonic
2020-11-24T19:30:14.118574image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
016194.9%
 
91760.5%
 
161730.5%
 
181700.5%
 
111690.5%
 
61670.5%
 
131650.5%
 
141650.5%
 
241630.5%
 
71600.5%
 
Other values (3607)2999390.6%
 
ValueCountFrequency (%) 
016194.9%
 
1430.1%
 
2860.3%
 
31030.3%
 
41160.4%
 
ValueCountFrequency (%) 
72982< 0.1%
 
69631< 0.1%
 
69381< 0.1%
 
67951< 0.1%
 
64561< 0.1%
 

65-74_years
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct3250
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean562.5635568
Minimum0
Maximum8129
Zeros1686
Zeros (%)5.1%
Memory size258.8 KiB
2020-11-24T19:30:14.249722image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q148
median189
Q3795
95-th percentile2265
Maximum8129
Range8129
Interquartile range (IQR)747

Descriptive statistics

Standard deviation781.5950408
Coefficient of variation (CV)1.389345313
Kurtosis4.328286354
Mean562.5635568
Median Absolute Deviation (MAD)174
Skewness1.978517976
Sum18632105
Variance610890.8078
MonotocityNot monotonic
2020-11-24T19:30:14.376808image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
016865.1%
 
141920.6%
 
81880.6%
 
131840.6%
 
101810.5%
 
151810.5%
 
61790.5%
 
91770.5%
 
161750.5%
 
71690.5%
 
Other values (3240)2980890.0%
 
ValueCountFrequency (%) 
016865.1%
 
1490.1%
 
21040.3%
 
31080.3%
 
41500.5%
 
ValueCountFrequency (%) 
81291< 0.1%
 
66871< 0.1%
 
63661< 0.1%
 
62711< 0.1%
 
61561< 0.1%
 

75-84_years
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct4091
Distinct (%)12.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean769.2380133
Minimum0
Maximum26787
Zeros1359
Zeros (%)4.1%
Memory size258.8 KiB
2020-11-24T19:30:14.505637image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q170
median266
Q31083
95-th percentile3085
Maximum26787
Range26787
Interquartile range (IQR)1013

Descriptive statistics

Standard deviation1078.771062
Coefficient of variation (CV)1.402389174
Kurtosis15.16947986
Mean769.2380133
Median Absolute Deviation (MAD)243
Skewness2.463015251
Sum25477163
Variance1163747.004
MonotocityNot monotonic
2020-11-24T19:30:14.631406image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
013594.1%
 
151460.4%
 
91450.4%
 
171450.4%
 
161380.4%
 
101330.4%
 
61320.4%
 
191300.4%
 
131280.4%
 
201260.4%
 
Other values (4081)3053892.2%
 
ValueCountFrequency (%) 
013594.1%
 
1250.1%
 
2560.2%
 
3800.2%
 
4930.3%
 
ValueCountFrequency (%) 
267871< 0.1%
 
102161< 0.1%
 
92071< 0.1%
 
91621< 0.1%
 
90291< 0.1%
 

85_years_or_more
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct2650
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean414.3955918
Minimum0
Maximum11167
Zeros2234
Zeros (%)6.7%
Memory size258.8 KiB
2020-11-24T19:30:14.756253image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q135
median136
Q3556.25
95-th percentile1686.05
Maximum11167
Range11167
Interquartile range (IQR)521.25

Descriptive statistics

Standard deviation616.1418221
Coefficient of variation (CV)1.486844538
Kurtosis14.50176577
Mean414.3955918
Median Absolute Deviation (MAD)125
Skewness2.801041921
Sum13724782
Variance379630.745
MonotocityNot monotonic
2020-11-24T19:30:14.875295image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
022346.7%
 
92420.7%
 
122290.7%
 
142130.6%
 
102100.6%
 
82090.6%
 
72080.6%
 
52020.6%
 
132020.6%
 
112010.6%
 
Other values (2640)2897087.5%
 
ValueCountFrequency (%) 
022346.7%
 
1710.2%
 
21310.4%
 
31580.5%
 
41840.6%
 
ValueCountFrequency (%) 
111671< 0.1%
 
90001< 0.1%
 
88381< 0.1%
 
88021< 0.1%
 
78581< 0.1%
 

households
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct1527
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean181.4393116
Minimum0
Maximum4074
Zeros4600
Zeros (%)13.9%
Memory size258.8 KiB
2020-11-24T19:30:14.998969image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19
median48
Q3226
95-th percentile798
Maximum4074
Range4074
Interquartile range (IQR)217

Descriptive statistics

Standard deviation298.0781528
Coefficient of variation (CV)1.642853195
Kurtosis15.18136631
Mean181.4393116
Median Absolute Deviation (MAD)48
Skewness3.062217552
Sum6009270
Variance88850.58516
MonotocityNot monotonic
2020-11-24T19:30:15.122792image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0460013.9%
 
24901.5%
 
84541.4%
 
44511.4%
 
94481.4%
 
64411.3%
 
74321.3%
 
34231.3%
 
54101.2%
 
103891.2%
 
Other values (1517)2458274.2%
 
ValueCountFrequency (%) 
0460013.9%
 
12730.8%
 
24901.5%
 
34231.3%
 
44511.4%
 
ValueCountFrequency (%) 
40741< 0.1%
 
40521< 0.1%
 
38551< 0.1%
 
38481< 0.1%
 
37921< 0.1%
 

$9,999_or_less
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct10474
Distinct (%)31.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3567.898521
Minimum0
Maximum43456
Zeros571
Zeros (%)1.7%
Memory size258.8 KiB
2020-11-24T19:30:15.257648image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile37
Q1273
median1059.5
Q34932.25
95-th percentile14861
Maximum43456
Range43456
Interquartile range (IQR)4659.25

Descriptive statistics

Standard deviation5120.549026
Coefficient of variation (CV)1.435172272
Kurtosis4.041200396
Mean3567.898521
Median Absolute Deviation (MAD)963.5
Skewness1.979055513
Sum118168799
Variance26220022.33
MonotocityNot monotonic
2020-11-24T19:30:15.376689image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
05711.7%
 
61540.2%
 
32530.2%
 
106510.2%
 
91490.1%
 
53490.1%
 
81490.1%
 
78470.1%
 
29470.1%
 
66460.1%
 
Other values (10464)3210496.9%
 
ValueCountFrequency (%) 
05711.7%
 
12< 0.1%
 
25< 0.1%
 
39< 0.1%
 
412< 0.1%
 
ValueCountFrequency (%) 
434561< 0.1%
 
380191< 0.1%
 
373811< 0.1%
 
367541< 0.1%
 
360091< 0.1%
 

$10,000-$14,999
Categorical

HIGH CARDINALITY

Distinct523
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size258.8 KiB
0
2898 
-
 
571
4.8
 
342
4.5
 
340
3.6
 
333
Other values (518)
28636 
ValueCountFrequency (%) 
028988.8%
 
-5711.7%
 
4.83421.0%
 
4.53401.0%
 
3.63331.0%
 
3.83281.0%
 
3.73231.0%
 
4.23181.0%
 
4.43171.0%
 
3.23140.9%
 
Other values (513)2703681.6%
 
2020-11-24T19:30:15.801381image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique106 ?
Unique (%)0.3%
2020-11-24T19:30:15.921150image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length3
Mean length2.834178744
Min length1

$15,000-$24,999
Categorical

HIGH CARDINALITY

Distinct419
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size258.8 KiB
0
3161 
-
 
571
3.2
 
376
4.5
 
376
2.9
 
374
Other values (414)
28262 
ValueCountFrequency (%) 
031619.5%
 
-5711.7%
 
3.23761.1%
 
4.53761.1%
 
2.93741.1%
 
4.23721.1%
 
4.83671.1%
 
4.93661.1%
 
3.13611.1%
 
4.43581.1%
 
Other values (409)2643879.8%
 
2020-11-24T19:30:16.053753image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique105 ?
Unique (%)0.3%
2020-11-24T19:30:16.171447image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length3
Mean length2.732216184
Min length1

$25,000-$34,999
Categorical

HIGH CARDINALITY

Distinct554
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size258.8 KiB
0
 
1658
-
 
571
10.2
 
238
9.4
 
238
11.3
 
237
Other values (549)
30178 
ValueCountFrequency (%) 
016585.0%
 
-5711.7%
 
10.22380.7%
 
9.42380.7%
 
11.32370.7%
 
9.12330.7%
 
12.72320.7%
 
11.42310.7%
 
11.52300.7%
 
9.82280.7%
 
Other values (544)2902487.6%
 
2020-11-24T19:30:16.291343image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique122 ?
Unique (%)0.4%
2020-11-24T19:30:16.411706image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length3
Mean length3.232669082
Min length1

$35,000-$49,999
Categorical

HIGH CARDINALITY

Distinct520
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size258.8 KiB
0
 
1706
-
 
571
10.4
 
338
11.1
 
310
9.9
 
303
Other values (515)
29892 
ValueCountFrequency (%) 
017065.2%
 
-5711.7%
 
10.43381.0%
 
11.13100.9%
 
9.93030.9%
 
10.32990.9%
 
12.52970.9%
 
11.92960.9%
 
11.42950.9%
 
102910.9%
 
Other values (510)2841485.8%
 
2020-11-24T19:30:16.539753image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique109 ?
Unique (%)0.3%
2020-11-24T19:30:16.663012image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length3
Mean length3.218719807
Min length1

$50,000-$64,999
Categorical

HIGH CARDINALITY

Distinct564
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size258.8 KiB
0
 
1339
-
 
571
14.3
 
309
14.6
 
303
12.9
 
302
Other values (559)
30296 
ValueCountFrequency (%) 
013394.0%
 
-5711.7%
 
14.33090.9%
 
14.63030.9%
 
12.93020.9%
 
13.13010.9%
 
15.43000.9%
 
14.42970.9%
 
15.12940.9%
 
132940.9%
 
Other values (554)2881087.0%
 
2020-11-24T19:30:16.791979image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique117 ?
Unique (%)0.4%
2020-11-24T19:30:16.910091image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length4
Mean length3.463013285
Min length1

$65,000-$74,999
Categorical

HIGH CARDINALITY

Distinct615
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size258.8 KiB
0
 
1095
-
 
571
19.3
 
283
17.9
 
281
18.1
 
277
Other values (610)
30613 
ValueCountFrequency (%) 
010953.3%
 
-5711.7%
 
19.32830.9%
 
17.92810.8%
 
18.12770.8%
 
17.42720.8%
 
18.82700.8%
 
17.52650.8%
 
18.22650.8%
 
182640.8%
 
Other values (605)2927788.4%
 
2020-11-24T19:30:17.027794image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique110 ?
Unique (%)0.3%
2020-11-24T19:30:17.139315image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length4
Mean length3.590368357
Min length1

$75,000-$99,999
Categorical

HIGH CARDINALITY

Distinct507
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size258.8 KiB
0
 
1908
-
 
571
11.2
 
295
13.4
 
293
11.1
 
287
Other values (502)
29766 
ValueCountFrequency (%) 
019085.8%
 
-5711.7%
 
11.22950.9%
 
13.42930.9%
 
11.12870.9%
 
122860.9%
 
10.92810.8%
 
12.52800.8%
 
142790.8%
 
11.42760.8%
 
Other values (497)2836485.6%
 
2020-11-24T19:30:17.266107image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique113 ?
Unique (%)0.3%
2020-11-24T19:30:17.390029image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length4
Mean length3.282971014
Min length1

$100,000_or_more
Categorical

HIGH CARDINALITY

Distinct831
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size258.8 KiB
#VALUE!
 
571
0
 
347
100
 
210
50
 
203
46.2
 
185
Other values (826)
31604 
ValueCountFrequency (%) 
#VALUE!5711.7%
 
03471.0%
 
1002100.6%
 
502030.6%
 
46.21850.6%
 
46.31750.5%
 
46.71740.5%
 
47.61710.5%
 
45.11690.5%
 
45.81650.5%
 
Other values (821)3075092.8%
 
2020-11-24T19:30:17.516299image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique90 ?
Unique (%)0.3%
2020-11-24T19:30:17.631170image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length7
Median length4
Mean length3.812439614
Min length1

median_household_income
Categorical

HIGH CARDINALITY

Distinct19384
Distinct (%)58.5%
Missing0
Missing (%)0.0%
Memory size258.8 KiB
-
 
1090
(X)
 
963
43750
 
79
41250
 
76
46250
 
72
Other values (19379)
30840 
ValueCountFrequency (%) 
-10903.3%
 
(X)9632.9%
 
43750790.2%
 
41250760.2%
 
46250720.2%
 
48750640.2%
 
47500630.2%
 
53750610.2%
 
38750610.2%
 
51250580.2%
 
Other values (19374)3053392.2%
 
2020-11-24T19:30:17.780827image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique14676 ?
Unique (%)44.3%
2020-11-24T19:30:17.898763image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length8
Median length5
Mean length4.850030193
Min length1

mean_household_income
Categorical

HIGH CARDINALITY

Distinct25781
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Memory size258.8 KiB
-
 
577
N
 
529
54570
 
6
61829
 
6
58551
 
5
Other values (25776)
31997 
ValueCountFrequency (%) 
-5771.7%
 
N5291.6%
 
545706< 0.1%
 
618296< 0.1%
 
585515< 0.1%
 
600915< 0.1%
 
591455< 0.1%
 
608305< 0.1%
 
491275< 0.1%
 
613075< 0.1%
 
Other values (25771)3197296.5%
 
2020-11-24T19:30:18.058370image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique20652 ?
Unique (%)62.4%
2020-11-24T19:30:18.171860image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length7
Median length5
Mean length4.963586957
Min length1

Interactions

2020-11-24T19:29:35.340259image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:35.440279image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:35.544444image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:35.649687image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:35.754906image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:35.854668image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:35.957491image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:36.058422image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:36.158172image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:36.263656image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:36.371907image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:36.477553image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:36.586662image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:36.686808image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:36.787548image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:36.894984image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:36.992414image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:37.096148image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:37.205247image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:37.315573image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:37.424969image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:37.528401image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:37.730817image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:37.834346image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:37.937729image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:38.047507image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:38.160618image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:38.270084image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:38.381196image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:38.485688image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:38.589597image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:38.699962image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:38.801900image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:38.908590image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:39.018924image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:39.130978image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:39.241931image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:39.348126image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:39.457146image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:39.565442image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:39.673048image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:39.785244image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:39.900755image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:40.012619image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:40.126475image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:40.233796image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:40.341239image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:40.454841image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:40.560714image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:40.667868image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:40.777362image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:40.889235image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:41.000666image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:41.109285image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:41.218799image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:41.325242image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:41.432374image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:41.545467image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:41.662426image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:41.777342image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:41.895844image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:42.004111image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:42.230028image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:29:42.346854image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
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Correlations

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Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
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Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
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Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-11-24T19:30:18.854747image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2020-11-24T19:30:05.937572image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-24T19:30:11.092106image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Sample

First rows

zipcode5_years_or_less5-9_years10-14_years15-19_years20-24_years25-34_years35-44_years45-54_years55-59_years60-64_years65-74_years75-84_years85_years_or_morehouseholds$9,999_or_less$10,000-$14,999$15,000-$24,999$25,000-$34,999$35,000-$49,999$50,000-$64,999$65,000-$74,999$75,000-$99,999$100,000_or_moremedian_household_incomemean_household_income
06011798210061080134213521321225321492434122910941628781313597248.11212.88.68.76.21.416.31081620349
1602402602006244024212953286551245139594725732905368315816231296831.416.317.912.210.67.72.921.21607923282
260352408266431773351368535856473677566783135364156632834747186743114.917.511.710.88.72.421.91680426820
36066331347331461474469707933776246585582260160191545.310.22011.7111.8012.81251215730
461028328143814902044212219853358377838581749175128751457423940426.914.823.715.29.37.51.618.41747523360
56126481636023536449747154732766879118690355440366557363316852297134.11119.311.39.69.73.122.41722925590
6616107075744585806477121292153315026675471363562270363636.617.415.913.310.12.32.314.71370520605
76172479314271597178317571719327634982975128615062325120344183523612.920.312.67.77.12.2171536121487
86227425381468479534468740846875507492956574105255736.112.71811.67.96.82.917.61568929228
9623429552121260827072970273447826194559626462385462226329581455833.512.520.8109.38.82.220.31659324732

Last rows

zipcode5_years_or_less5-9_years10-14_years15-19_years20-24_years25-34_years35-44_years45-54_years55-59_years60-64_years65-74_years75-84_years85_years_or_morehouseholds$9,999_or_less$10,000-$14,999$15,000-$24,999$25,000-$34,999$35,000-$49,999$50,000-$64,999$65,000-$74,999$75,000-$99,999$100,000_or_moremedian_household_incomemean_household_income
331109990322000200000128001100009.1090.9100-N
331119991816200132019247471461208510.6011.812.915.314.130.6604687554634
331129991963757303547178679102416076253048.92.312.810.96.924.314.545.75267962625
33113999211950881381491501282332373461841261333266735.63.67.612.814.612.511.738.86190874638
331149992227714831258322360218212421090.97.330.316.518.310.18.336.73125048712
331159992313000000006007013046.253.800000-N
33116999258266550473660868211167878136183257.16.221.211.112.617.59.539.63859452706
33117999261711161124140113107224182236161991174074765.51.914.111.116.814.51243.35107171580
33118999271230000003222362013007828.2023.115.425.60025.61986135617
33119999292365891031331421002231973812782112512154211165.16.914.29.915.117.613.646.34794162587